Computer Vision is one of the most exciting fields in Machine Learning and AI. It has applications in many industries, such as self-driving cars, robotics, augmented reality, and much more. In this beginner-friendly course, you will understand computer vision and learn about its various applications across many industries.
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À propos de ce cours
Compétences que vous acquerrez
- Deep Learning
- Opencv
- Artificial Intelligence (AI)
- Image Processing
- Computer Vision
Offert par

IBM
IBM is the global leader in business transformation through an open hybrid cloud platform and AI, serving clients in more than 170 countries around the world. Today 47 of the Fortune 50 Companies rely on the IBM Cloud to run their business, and IBM Watson enterprise AI is hard at work in more than 30,000 engagements. IBM is also one of the world’s most vital corporate research organizations, with 28 consecutive years of patent leadership. Above all, guided by principles for trust and transparency and support for a more inclusive society, IBM is committed to being a responsible technology innovator and a force for good in the world.
Programme de cours : ce que vous apprendrez dans ce cours
Introduction to Computer Vision
In this module, we will discuss the rapidly developing field of image processing. In addition to being the first step in Computer Vision, it has broad applications ranging anywhere from making your smartphone's image look crystal clear to helping doctors cure diseases.
Image Processing with OpenCV and Pillow
Image processing enhances images or extracts useful information from the image. In this module, we will learn the basics of image processing with Python libraries OpenCV and Pillow.
Machine Learning Image Classification
In this module, you will Learn About the different Machine learning classification Methods commonly used for Computer vision, including k nearest neighbours, Logistic regression, SoftMax Regression and Support Vector Machines. Finally, you will learn about Image features.
Neural Networks and Deep Learning for Image Classification
In this module, you will learn about Neural Networks, fully connected Neural Networks, and Convolutional Neural Network (CNN). You will learn about different components such as Layers and different types of activation functions such as ReLU. You also get to know the different CNN Architecture such as ResNet and LenNet.
Avis
- 5 stars65,54 %
- 4 stars20,59 %
- 3 stars6,74 %
- 2 stars3,12 %
- 1 star3,99 %
Meilleurs avis pour INTRODUCTION TO COMPUTER VISION AND IMAGE PROCESSING
Great introduction to Visual Recognition and Computer Vision! Lots of examples are provided for me to grasp the concepts behind complicated applications!
Some of these modules need to fix some errors that exist on the IBM Cloud. Had to constantly look for discussions that open topics on what needs to be worked on.
This course was a lot of fun and I really enjoyed it!! I'm excited to pursue a new career in this exciting field.
The course is well designed. The only issue I have witnessed was during running LAB in Jupyter Notebook, I hope it will be fixed soon.
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